{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\Han\Desktop\document\불평등 연구\주제10_세대별 성평등\social sciences\data\analysis_1.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}30 Nov 2024, 03:06:02

{com}. reg gender_inequality c.age##i.gender income education occupation spouse child appearance satisfaction i.year

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     9,587
{txt}{hline 13}{c +}{hline 34}   F(11, 9575)     = {res}   105.73
{txt}       Model {c |} {res} 1991.24363        11  181.022148   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 16393.6515     9,575  1.71213071   {txt}R-squared       ={res}    0.1083
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1073
{txt}       Total {c |} {res} 18384.8952     9,586  1.91789017   {txt}Root MSE        =   {res} 1.3085

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}gender_ine~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2} .1103729{col 26}{space 2} .0174352{col 37}{space 1}    6.33{col 46}{space 3}0.000{col 54}{space 4} .0761963{col 67}{space 3} .1445496
{txt}{space 4}1.gender {c |}{col 14}{res}{space 2} 1.472854{col 26}{space 2} .0744227{col 37}{space 1}   19.79{col 46}{space 3}0.000{col 54}{space 4}  1.32697{col 67}{space 3} 1.618739
{txt}{space 12} {c |}
gender#c.age {c |}
{space 10}1  {c |}{col 14}{res}{space 2}-.2137694{col 26}{space 2} .0211775{col 37}{space 1}  -10.09{col 46}{space 3}0.000{col 54}{space 4}-.2552817{col 67}{space 3}-.1722571
{txt}{space 12} {c |}
{space 6}income {c |}{col 14}{res}{space 2}-.0222997{col 26}{space 2} .0135186{col 37}{space 1}   -1.65{col 46}{space 3}0.099{col 54}{space 4}-.0487989{col 67}{space 3} .0041995
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.1172865{col 26}{space 2} .0250595{col 37}{space 1}   -4.68{col 46}{space 3}0.000{col 54}{space 4}-.1664084{col 67}{space 3}-.0681646
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0827417{col 26}{space 2}  .036075{col 37}{space 1}   -2.29{col 46}{space 3}0.022{col 54}{space 4}-.1534564{col 67}{space 3} -.012027
{txt}{space 6}spouse {c |}{col 14}{res}{space 2}-.1131742{col 26}{space 2}  .031442{col 37}{space 1}   -3.60{col 46}{space 3}0.000{col 54}{space 4}-.1748071{col 67}{space 3}-.0515412
{txt}{space 7}child {c |}{col 14}{res}{space 2} -.285913{col 26}{space 2} .0273237{col 37}{space 1}  -10.46{col 46}{space 3}0.000{col 54}{space 4}-.3394733{col 67}{space 3}-.2323526
{txt}{space 2}appearance {c |}{col 14}{res}{space 2}-.1156617{col 26}{space 2} .0397565{col 37}{space 1}   -2.91{col 46}{space 3}0.004{col 54}{space 4}-.1935929{col 67}{space 3}-.0377305
{txt}satisfaction {c |}{col 14}{res}{space 2} .0286042{col 26}{space 2} .0071941{col 37}{space 1}    3.98{col 46}{space 3}0.000{col 54}{space 4} .0145023{col 67}{space 3} .0427061
{txt}{space 12} {c |}
{space 8}year {c |}
{space 7}2021  {c |}{col 14}{res}{space 2} .3366556{col 26}{space 2} .0560752{col 37}{space 1}    6.00{col 46}{space 3}0.000{col 54}{space 4} .2267363{col 67}{space 3} .4465749
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 3.606604{col 26}{space 2} .0833492{col 37}{space 1}   43.27{col 46}{space 3}0.000{col 54}{space 4} 3.443221{col 67}{space 3} 3.769986
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. 
. margins gender , at( age =(1(1)5)) atmeans noatlegend
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     9,587
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}_at#gender {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} 3.586882{col 26}{space 2} .0439641{col 37}{space 1}   81.59{col 46}{space 3}0.000{col 54}{space 4} 3.500703{col 67}{space 3} 3.673061
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} 4.845967{col 26}{space 2} .0404495{col 37}{space 1}  119.80{col 46}{space 3}0.000{col 54}{space 4} 4.766677{col 67}{space 3} 4.925256
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} 3.697255{col 26}{space 2} .0297346{col 37}{space 1}  124.34{col 46}{space 3}0.000{col 54}{space 4} 3.638969{col 67}{space 3} 3.755541
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2}  4.74257{col 26}{space 2} .0272848{col 37}{space 1}  173.82{col 46}{space 3}0.000{col 54}{space 4} 4.689086{col 67}{space 3} 4.796054
{txt}{space 8}3 0  {c |}{col 14}{res}{space 2} 3.807628{col 26}{space 2} .0210577{col 37}{space 1}  180.82{col 46}{space 3}0.000{col 54}{space 4}  3.76635{col 67}{space 3} 3.848905
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} 4.639174{col 26}{space 2} .0185313{col 37}{space 1}  250.34{col 46}{space 3}0.000{col 54}{space 4} 4.602848{col 67}{space 3} 4.675499
{txt}{space 8}4 0  {c |}{col 14}{res}{space 2} 3.918001{col 26}{space 2} .0247119{col 37}{space 1}  158.55{col 46}{space 3}0.000{col 54}{space 4}  3.86956{col 67}{space 3} 3.966441
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} 4.535777{col 26}{space 2}  .020809{col 37}{space 1}  217.97{col 46}{space 3}0.000{col 54}{space 4} 4.494987{col 67}{space 3} 4.576567
{txt}{space 8}5 0  {c |}{col 14}{res}{space 2} 4.028374{col 26}{space 2} .0372276{col 37}{space 1}  108.21{col 46}{space 3}0.000{col 54}{space 4} 3.955399{col 67}{space 3} 4.101348
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} 4.432381{col 26}{space 2} .0318319{col 37}{space 1}  139.24{col 46}{space 3}0.000{col 54}{space 4} 4.369984{col 67}{space 3} 4.494778
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. 
. marginsplot, recastci(rarea)

{text}{p 2 6 2}Variables that uniquely identify margins: age gender{p_end}
{res}
{com}. interflex gender_inequality gender age income education occupation spouse child appearance satisfaction, ylab(Gender inequality) dlab(Gender) xlab(Age) fe(year )
{res}Fixed effects included; clustered standard errors highly recommended
{txt}p value of Wald test: {res}0.0000

{com}. reg gender_inequality_prospect c.age##i.gender income education occupation spouse child appearance satisfaction i.year

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     9,587
{txt}{hline 13}{c +}{hline 34}   F(11, 9575)     = {res}    76.22
{txt}       Model {c |} {res} 1196.05752        11  108.732502   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  13659.829     9,575  1.42661399   {txt}R-squared       ={res}    0.0805
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0795
{txt}       Total {c |} {res} 14855.8865     9,586  1.54974823   {txt}Root MSE        =   {res} 1.1944

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}gender_ine~t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}age {c |}{col 14}{res}{space 2} .1057615{col 26}{space 2} .0159152{col 37}{space 1}    6.65{col 46}{space 3}0.000{col 54}{space 4} .0745644{col 67}{space 3} .1369586
{txt}{space 4}1.gender {c |}{col 14}{res}{space 2} 1.276901{col 26}{space 2} .0679344{col 37}{space 1}   18.80{col 46}{space 3}0.000{col 54}{space 4} 1.143735{col 67}{space 3} 1.410067
{txt}{space 12} {c |}
gender#c.age {c |}
{space 10}1  {c |}{col 14}{res}{space 2}-.2026711{col 26}{space 2} .0193312{col 37}{space 1}  -10.48{col 46}{space 3}0.000{col 54}{space 4}-.2405644{col 67}{space 3}-.1647779
{txt}{space 12} {c |}
{space 6}income {c |}{col 14}{res}{space 2}-.0371229{col 26}{space 2}   .01234{col 37}{space 1}   -3.01{col 46}{space 3}0.003{col 54}{space 4}-.0613119{col 67}{space 3}-.0129339
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0954911{col 26}{space 2} .0228748{col 37}{space 1}   -4.17{col 46}{space 3}0.000{col 54}{space 4}-.1403305{col 67}{space 3}-.0506516
{txt}{space 2}occupation {c |}{col 14}{res}{space 2}-.0365763{col 26}{space 2}   .03293{col 37}{space 1}   -1.11{col 46}{space 3}0.267{col 54}{space 4}-.1011261{col 67}{space 3} .0279734
{txt}{space 6}spouse {c |}{col 14}{res}{space 2}-.1099488{col 26}{space 2} .0287008{col 37}{space 1}   -3.83{col 46}{space 3}0.000{col 54}{space 4}-.1662086{col 67}{space 3}-.0536891
{txt}{space 7}child {c |}{col 14}{res}{space 2}-.1521678{col 26}{space 2} .0249416{col 37}{space 1}   -6.10{col 46}{space 3}0.000{col 54}{space 4}-.2010587{col 67}{space 3}-.1032769
{txt}{space 2}appearance {c |}{col 14}{res}{space 2}-.0218349{col 26}{space 2} .0362905{col 37}{space 1}   -0.60{col 46}{space 3}0.547{col 54}{space 4} -.092972{col 67}{space 3} .0493022
{txt}satisfaction {c |}{col 14}{res}{space 2} .0343398{col 26}{space 2} .0065669{col 37}{space 1}    5.23{col 46}{space 3}0.000{col 54}{space 4} .0214673{col 67}{space 3} .0472122
{txt}{space 12} {c |}
{space 8}year {c |}
{space 7}2021  {c |}{col 14}{res}{space 2}  .171581{col 26}{space 2} .0511865{col 37}{space 1}    3.35{col 46}{space 3}0.001{col 54}{space 4} .0712445{col 67}{space 3} .2719174
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 4.325325{col 26}{space 2} .0760828{col 37}{space 1}   56.85{col 46}{space 3}0.000{col 54}{space 4} 4.176187{col 67}{space 3} 4.474464
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. 
. margins gender , at( age =(1(1)5)) atmeans noatlegend
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     9,587
{txt}Model VCE{col 14}: {res}OLS

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}_at#gender {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} 4.333006{col 26}{space 2} .0401312{col 37}{space 1}  107.97{col 46}{space 3}0.000{col 54}{space 4}  4.25434{col 67}{space 3} 4.411671
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} 5.407235{col 26}{space 2} .0369231{col 37}{space 1}  146.45{col 46}{space 3}0.000{col 54}{space 4} 5.334858{col 67}{space 3} 5.479612
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} 4.438767{col 26}{space 2} .0271423{col 37}{space 1}  163.54{col 46}{space 3}0.000{col 54}{space 4} 4.385563{col 67}{space 3} 4.491972
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} 5.310326{col 26}{space 2} .0249061{col 37}{space 1}  213.21{col 46}{space 3}0.000{col 54}{space 4} 5.261505{col 67}{space 3} 5.359147
{txt}{space 8}3 0  {c |}{col 14}{res}{space 2} 4.544529{col 26}{space 2} .0192219{col 37}{space 1}  236.42{col 46}{space 3}0.000{col 54}{space 4}  4.50685{col 67}{space 3} 4.582208
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} 5.213416{col 26}{space 2} .0169157{col 37}{space 1}  308.20{col 46}{space 3}0.000{col 54}{space 4} 5.180258{col 67}{space 3} 5.246575
{txt}{space 8}4 0  {c |}{col 14}{res}{space 2}  4.65029{col 26}{space 2} .0225575{col 37}{space 1}  206.15{col 46}{space 3}0.000{col 54}{space 4} 4.606073{col 67}{space 3} 4.694508
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} 5.116507{col 26}{space 2} .0189948{col 37}{space 1}  269.36{col 46}{space 3}0.000{col 54}{space 4} 5.079273{col 67}{space 3}  5.15374
{txt}{space 8}5 0  {c |}{col 14}{res}{space 2} 4.756052{col 26}{space 2} .0339821{col 37}{space 1}  139.96{col 46}{space 3}0.000{col 54}{space 4}  4.68944{col 67}{space 3} 4.822664
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} 5.019597{col 26}{space 2} .0290568{col 37}{space 1}  172.75{col 46}{space 3}0.000{col 54}{space 4}  4.96264{col 67}{space 3} 5.076554
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. 
. marginsplot, recastci(rarea)

{text}{p 2 6 2}Variables that uniquely identify margins: age gender{p_end}
{res}
{com}. interflex gender_inequality_prospect gender age income education occupation spouse child appearance satisfaction, ylab(Gender inequality) dlab(Gender) xlab(Age) fe(year )
{res}Fixed effects included; clustered standard errors highly recommended
{txt}p value of Wald test: {res}0.0000

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\Han\Desktop\document\불평등 연구\주제10_세대별 성평등\social sciences\data\analysis_1.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}30 Nov 2024, 03:06:44
{txt}{.-}
{smcl}
{txt}{sf}{ul off}